Model and Agent Runtime

Models in NativelyAI are treated as governed execution resources.

Organizations run open-source, proprietary, or fine-tuned models inside infrastructure they control. Model versions are pinned, execution is reproducible, and fallback behavior is defined explicitly through policy.

Agents operate as policy-bound actors shaped by declared execution intent.

Every action flows from explicit goals, scopes, budgets, and constraints defined by the user.

Authority is fixed by policy and cannot expand beyond the intent that created it.

This keeps multi-step systems predictable, auditable, and safe, even when agents reason, plan, and coordinate complex workflows.